In Multi-access Edge Computing networks, services can be deployed on nearby edge clouds (EC) as service function chains (SFCs) to meet strict quality of service (QoS) requirements. As users move, frequent SFC reconfigurations are required, but these are non-trivial: SFCs can serve users only when all required virtual network functions (VNFs) are available, and VNFs undergo time-consuming lifecycle operations before becoming operational. We show that ignoring lifecycle dynamics oversimplifies deployment, jeopardizes QoS, and must be avoided in practical SFC management. To address this, forecasts of user connectivity can be leveraged to proactively deploy VNFs and reconfigure SFCs. But forecasts are inherently imperfect, requiring lifecycle and connectivity uncertainty to be jointly considered. We present RIPPLE, a lifecycle-aware SFC embedding approach to deploy VNFs at the right time and location, reducing service interruptions. We show that RIPPLE closes the gap with solutions that unrealistically assume instantaneous lifecycle, even under realistic lifecycle constraints.

翻译：在多接入边缘计算网络中，服务可以以服务功能链的形式部署在邻近的边缘云上，以满足严格的服务质量要求。随着用户移动，需要频繁进行SFC重配置，但这一过程并非易事：SFC仅当所有必需的虚拟网络功能均可用时才能为用户提供服务，而VNF在进入可操作状态前需经历耗时的生命周期操作。我们证明，忽略生命周期动态性会使部署过程过度简化，危及服务质量，在实际SFC管理中必须避免。为解决此问题，可利用用户连接性预测来主动部署VNF并重配置SFC。但预测本身存在固有缺陷，需要同时考虑生命周期与连接性的不确定性。本文提出RIPPLE——一种生命周期感知的SFC嵌入方法，可在恰当的时间和位置部署VNF，从而减少服务中断。研究表明，即使在现实生命周期约束下，RIPPLE也能弥合与不切实际地假设瞬时生命周期的解决方案之间的差距。